Disease cluster detection methods: recent developments and public health implications

Methods for detecting spatial and spatiotemporal clusters of health and disease have advanced significantly in the past decade. This article reviews recent advances in four areas: spatial search processes, network-based methods, statistical analysis and modelling of local clusters and space-time cluster detection. I then turn to a more critical discussion of the implications of hotspot mapping for public health policy and intervention, highlighting the need to incorporate process-based understandings that impact spatial and social inequalities in ill health for particular health issues in particular geographic contexts.